Clust
Eval
clustering evaluation framework
Welcome
Overview
Clustering Methods
Data Sets
Measures
Submit
Advanced
Help
About us
Location:
Clustering Methods
»
Markov Clustering
»
Best Parameters
Navigation:
General
Best Qualities
Best Parameters
Hints:
Which parameter sets lead to the optimal clustering quality?
Please choose a clustering quality measure:
Davies Bouldin Index (R)
Dunn Index (R)
F1-Score
F2-Score
False Discovery Rate
False Positive Rate
Fowlkes Mallows Index (R)
Jaccard Index (R)
Rand Index
Rand Index (R)
Sensitivity
Silhouette Value (R)
Specificity
V-Measure
Dataset
Best quality
Parameter set
brown
0.988
I=2.1512512512512516
chang_pathbased
0.647
I=9.385285285285285
ppi_mips
0.839
I=5.028828828828829
chang_spiral
0.576
I=5.42082082082082
astral_40_strsim
0.466
I=4.85955955955956
astral_40_seqsim_beh
0.514
I=1.385085085085085
fraenti_s3
0.258
I=8.280580580580581
bone_marrow_fixLabels
0.601
I=1.1979979979979982
fu_flame
0.732
I=3.5855855855855854
coli_state
0.625
I=2.177977977977978
coli_find
0.356
I=7.077877877877879
coli_need
0.622
I=3.6212212212212216
coli_time
0.513
I=6.587887887887889
gionis_aggregation
0.465
I=1.1
veenman_r15
0.255
I=4.253753753753754
zahn_compound
0.497
I=5.465365365365365
synthetic_spirals
0.706
I=4.12012012012012
synthetic_cassini
0.598
I=2.7036036036036037
twonorm_100d
0.705
I=2.7926926926926927
twonorm_50d
0.705
I=2.4096096096096096
synthetic_cuboid
0.511
I=7.166966966966968
astral1_161
0.465
I=2.365065065065065
tcga
0.744
I=1.2336336336336338
bone_marrow
0.783
I=9.955455455455455
zachary
1.0
I=1.8483483483483483